COVID-19 and Personal Protective Equipment-Related Challenges Faced by Pediatric Dentists during patient care: A Qualitative Study
Bibliographic record
Abstract
Objective: To describe the challenges pediatric dentists face while caring for their patients during the pandemic. Material and Methods: A descriptive qualitative study was conducted with purposefully sampled pediatric dentists. Data were collected through in-depth, semi-structured interviews until the content of the collected data reached theoretical saturation. Data were transcribed verbatim, coded, and analyzed using content analyses. Results: Seven participants (four females and three males) between 29 and 50 years participated in the study. Three themes emerged from the analyses: Anxiety and fear; PPE (Personal Protective Equipment) and its impact on care delivery; and 3) Behavior management. Conclusion: Dental care delivery was challenging for pediatric dentists. They experienced high anxiety levels and modified their services according to the recommended guidelines while making accommodations to lessen patients’ COVID-19-related anxiety. The additional mandated PPE use affected the communication between the dentists and their patients, affecting their dentist-patient bonding.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".